scholarly journals On Interactive Pattern Mining from Relational Databases

2007 ◽  
pp. 42-62 ◽  
Author(s):  
Francesco Bonchi ◽  
Fosca Giannotti ◽  
Claudio Lucchese ◽  
Salvatore Orlando ◽  
Raffaele Perego ◽  
...  
Keyword(s):  
Relational Databases ◽  
Pattern Mining

Distributed Mining of Closed Patterns from Multi-Relational Data

2015 ◽  
Vol 19 (6) ◽  
pp. 804-809 ◽  
Author(s):  
Yohei Kamiya ◽  
◽  
Hirohisa Seki
Keyword(s):  
Inductive Logic Programming ◽  
Formal Concept Analysis ◽  
Relational Databases ◽  
Pattern Mining ◽  
Inductive Logic ◽  
Relational Data ◽  
Formal Concept ◽  
Global Database ◽  
Closed Pattern ◽  
Closed Pattern Mining

In multi-relational data mining (MRDM), there have been proposed many methods for searching for patterns that involve multiple tables (relations) from a relational database. In this paper, we consider closed pattern mining from distributed multi-relational databases (MRDBs). Since the computation of MRDM is costly compared with the conventional itemset mining, we propose some efficient methods for computing closed patterns using the techniques studied in Inductive Logic Programming (ILP) and Formal Concept Analysis (FCA). Given a set oflocaldatabases, we first compute sets of their closed patterns (concepts) using a closed pattern mining algorithm tailored to MRDM, and then generate the set of closed patterns in the global database by utilizing themergeoperator. We also present some experimental results, which shows the effectiveness of the proposed methods.

An Adaptive Data Distribution Through Tree Rules in Frequent Pattern Mining

2018 ◽  
pp. 300-305
Keyword(s):  
Information Sharing ◽  
Pattern Mining ◽  
Data Distribution ◽  
Frequent Pattern Mining ◽  
Frequent Pattern ◽  
General Development ◽  
Secure Information ◽  
Evaluation Parameters ◽  
Secure Information Sharing

Information sharing among the associations is a general development in a couple of zones like business headway and exhibiting. As bit of the touchy principles that ought to be kept private may be uncovered and such disclosure of delicate examples may impacts the advantages of the association that have the data. Subsequently the standards which are delicate must be secured before sharing the data. In this paper to give secure information sharing delicate guidelines are bothered first which was found by incessant example tree. Here touchy arrangement of principles are bothered by substitution. This kind of substitution diminishes the hazard and increment the utility of the dataset when contrasted with different techniques. Examination is done on certifiable dataset. Results shows that proposed work is better as appear differently in relation to various past strategies on the introduce of evaluation parameters.

924-P: Pattern Mining of Trajectories of Glucose Values of Continuous Glucose Monitoring System by Artificial Intelligence in Type 2 Diabetes Patients

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 924-P
Author(s):  
MASAKI MAKINO ◽  
RYO YOSHIMOTO ◽  
MIZUHO KONDO-ANDO ◽  
YASUMASA YOSHINO ◽  
IZUMI HIRATSUKA ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Type 2 Diabetes ◽  
Monitoring System ◽  
Continuous Glucose Monitoring ◽  
Pattern Mining ◽  
Glucose Monitoring ◽  
Continuous Glucose Monitoring System ◽  
Diabetes Patients

Review of Improvement of Web Search Based on Web Log File

2012 ◽  
Vol 3 (2) ◽  
pp. 298-300 ◽  
Author(s):  
Soniya P. Chaudhari ◽  
Prof. Hitesh Gupta ◽  
S. J. Patil
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Web Search ◽  
Pattern Mining ◽  
Efficiency Improvement ◽  
Web Searching ◽  
Important Method ◽  
Web Log ◽  
Journal Paper ◽  
Log File

In this paper we review various research of journal paper as Web Searching efficiency improvement. Some important method based on sequential pattern Mining. Some are based on supervised learning or unsupervised learning. And also used for other method such as Fuzzy logic and neural network

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